JMLR

JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes

Jonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash K. Mansinghka

Comments In Proceedings of the 32nd International Conference on Machine Learning (ICML 2015)

Journal ref JMLR: W&CP Volume 37, 2015 pp. 693-701

MADE: Masked Autoencoder for Distribution Estimation

Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle

Comments 9 pages and 1 page of supplementary material. Updated to match published version

Journal ref Proceedings of the 32nd International Conference on Machine Learning, JMLR W&CP 37:881-889, 2015

BayesPy: Variational Bayesian Inference in Python

Jaakko Luttinen

Comments Submitted to Journal of Machine Learning Research - Machine Learning Open Source Software

Efficient combination of pairswise feature networks

Pau Bellot, Patrick E. Meyer

Comments JMLR: Workshop and Conference Proceedings, 2014 Connectomics (ECML 2014)

Surrogate Functions for Maximizing Precision at the Top

Purushottam Kar, Harikrishna Narasimhan, Prateek Jain

Comments To appear in the the proceedings of the 32nd International Conference on Machine Learning (ICML 2015)

Journal ref Journal of Machine Learning Research, W&CP 37 (2015)

Optimizing Non-decomposable Performance Measures: A Tale of Two Classes

Harikrishna Narasimhan, Purushottam Kar, Prateek Jain

Comments To appear in proceedings of the 32nd International Conference on Machine Learning (ICML 2015)

Journal ref Journal of Machine Learning Research, W&CP 37 (2015)

Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares -- ICML

Garvesh Raskutti, Michael Mahoney

Comments 9 pages, Proceedings of the 32 nd International Conference on Machine Learning, Lille, France, 2015. JMLR

Distributed Gaussian Processes

Marc Peter Deisenroth, Jun Wei Ng

Comments 10 pages, 5 figures. Appears in Proceedings of ICML 2015

Journal ref JMLR W&CP, vol 37, 2015

Tensor Factorization via Matrix Factorization

Volodymyr Kuleshov, Arun Tejasvi Chaganty, Percy Liang

Comments Appearing in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 2015, San Diego, CA, USA. JMLR: W&CP volume 38

An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization

Necdet Serhat Aybat, Garud Iyengar, Zi Wang

Comments The manuscript will appear in the Proceedings of the 32nd International Conference on Machine Learning, Lille, France, 2015. JMLR: W&CP volume 37. Copyright 2015 by the author(s)

Building Classifiers to Predict the Start of Glucose-Lowering Pharmacotherapy Using Belgian Health Expenditure Data

Marc Claesen, Frank De Smet, Pieter Gillard, Chantal Mathieu, Bart De Moor

Comments 23 pages, 5 figures, submitted to JMLR special issue on Learning from Electronic Health Data

The Nataf-Beta Random Field Classifier: An Extension of the Beta Conjugate Prior to Classification Problems

James-A. Goulet

Comments 17 pages, 4 figures, Submitted for publication in the Journal of Machine Learning Research

Local Identification of Overcomplete Dictionaries

Karin Schnass

Comments 32 pages, 2 figures, final version accepted to JMLR

Efficient Active Learning of Halfspaces: an Aggressive Approach

Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz

Comments Full version of: Gonen, Sabato and Shalev-Shwartz, "Efficient Active Learning of Halfspaces: an Aggressive Approach", ICML 2013

Journal ref Journal of Machine Learning Research, 14(Sep):2487-2519, 2013

Random Feature Maps for Dot Product Kernels

Purushottam Kar, Harish Karnick

Comments To appear in the proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS 2012). This version corrects a minor error with Lemma 10. Acknowledgements : Devanshu Bhimwal

Journal ref Journal of Machine Learning Research, W&CP 22 (2012) 583-591

A Novel M-Estimator for Robust PCA

Teng Zhang, Gilad Lerman

Journal ref Journal of Machine Learning Research 15 (2014) 749-808

Machine Learning with Operational Costs

Theja Tulabandhula, Cynthia Rudin

Comments Current version: Final version appearing in JMLR 2013. v2: Many parts have been rewritten including the introduction, Minor correction of Theorem 6. 38 pages. Previously: v1: 36 pages, 8 figures. Short version appears in Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012

Multi-Instance Learning with Any Hypothesis Class

Sivan Sabato, Naftali Tishby

Comments Fixed typos and added some explanations

Journal ref Journal of Machine Learning Research 13(Oct):1999-3039, 2012

Machine Learning Markets

Amos Storkey

Comments Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics 2011

Journal ref Journal of Machine Learning Research W&CP 15(AISTATS):716-724, 2011

Positive Semidefinite Metric Learning Using Boosting-like Algorithms

Chunhua Shen, Junae Kim, Lei Wang, Anton van den Hengel

Comments 30 pages, appearing in Journal of Machine Learning Research

An Introduction to Artificial Prediction Markets for Classification

Adrian Barbu, Nathan Lay

Comments 29 pages, 8 figures

Journal ref Journal of Machine Learning Research, 13, 2177-2204, 2012

On the Bayes-optimality of F-measure maximizers

Willem Waegeman, Krzysztof Dembczynski, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hullermeier

Journal ref JMLR 15 (2014) 3333-3388

Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior

Debdeep Pati, Anirban Bhattacharya, Guang Cheng

Comments To appear in the Journal of Machine Learning Research

Ellipsoidal Rounding for Nonnegative Matrix Factorization Under Noisy Separability

Tomohiko Mizutani

Comments 29 pages, 6 figures. Minor revisions; Revised Figure 2; Added Table 1

Journal ref Journal of Machine Learning Research 15, pp. 1011-1039, 2014

Statistical topological data analysis using persistence landscapes

Peter Bubenik

Comments 26 pages, final version, to appear in Journal of Machine Learning Research, includes two additional examples not in the journal version: random geometric complexes and Erdos-Renyi random clique complexes

Journal ref Journal of Machine Learning Research, 16 (2015), 77-102

On the Complexity of A/B Testing

Emilie Kaufmann, Olivier Cappé, Aurélien Garivier

Journal ref Conference on Learning Theory, Jun 2014, Barcelona, Spain. JMLR: Workshop and Conference Proceedings, 35, pp.461-481

Particle Gibbs for Bayesian Additive Regression Trees

Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh

Journal ref Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 2015, San Diego, CA, USA. JMLR: W&CP volume 38

A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates

Yudong Chen, Xinyang Yi, Constantine Caramanis

Comments Added results on minimax lower bounds, which match our upper bounds on recovery errors up to log factors. Appeared in the Conference on Learning Theory (COLT), 2014. (JMLR W&CP 35 :560-604, 2014)

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering

Simon Lacoste-Julien, Fredrik Lindsten, Francis Bach

Comments in 18th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2015, San Diego, United States. 38, JMLR Workshop and Conference Proceedings

Feature Selection for Linear SVM with Provable Guarantees

Saurabh Paul, Malik Magdon-Ismail, Petros Drineas

Comments Appearing in Proceedings of 18th AISTATS, JMLR W&CP, vol 38, 2015